MétaCan
Menu
Back to cohort
Record W2103645799 · doi:10.1080/13854040500473760

Developing Clinically Suitable Measures of Social Cognition for Children: Initial Findings from a Normative Sample

2006· article· en· W2103645799 on OpenAlexaff
Jennifer Saltzman-Benaiah, Christopher E. Lalonde

Bibliographic record

VenueThe Clinical Neuropsychologist · 2006
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychologyNormativeSocial competenceCognitionDevelopmental psychologyAcquired brain injuryClinical psychologyCompetence (human resources)Autism spectrum disorderSocial cognitionAutismSocial changePsychiatryRehabilitationSocial psychology

Abstract

fetched live from OpenAlex

Our understanding of children's social competence has increased tremendously over the past two decades. There is increasing evidence to suggest that social-cognitive impairments are not restricted to children on the autistic spectrum, but rather may be associated with a host of developmental and acquired neurological conditions including learning disabilities, attention deficit disorder, traumatic brain injury, and stroke. Although many investigators have begun to bridge the gap between clinical practice and research by applying experimental tasks to clinical populations, few tools are available for the clinical evaluation of social competence, particularly in children. This study marks a series of first steps in the development of measures suitable for the assessment of children between 6 and 12 years of age. The results of the study provide data for a number of experimental tasks that have been adapted with clinical practice in mind. A discussion of the developmental progressions and the relationships among the measures is also included.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.219
GPT teacher head0.451
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Clinical NeuropsychologistSame topicAutism Spectrum Disorder ResearchFrench-language works237,207